Emerging Artificial Intelligence (AI) and Machine Learning (ML) innovations in Open RAN Massive MIMO (mMIMO) solutions will play a pivotal role in improving performance to match that of traditional RAN mMIMO, according to global technology intelligence firm ABI Research. While traditional RAN vendors currently dominate the mMIMO market, momentum for Open RAN is building as the technology matures, with pioneering deployments from operators like Rakuten and DISH.

“Advanced AI and ML techniques are poised to help close the performance gap by enhancing key capabilities such as beamforming and channel estimation,” states 5G, 6G and Open RAN Research Analyst Larbi Belkhit. “Integration of these models, likely in the Distributed Unit (DU), will be instrumental for Open RAN vendors to maximize spectrum efficiency.”

Companies such as DeepSig are already demonstrating that AI-powered software can improve Open RAN mMIMO efficiency. Its OmniPHY solution leverages ML for improved channel estimation, beam optimization, and interference mitigation in 5G networks. As AI/ML matures, such solutions applied to Open RAN mMIMO will boost performance and energy consumption closer to traditional RAN levels.

“The integration of AI and ML techniques, along with other innovations in energy efficiency and GPU acceleration, will accelerate performance improvements closer to traditional RAN networks. This will remove critical barriers to Open RAN adoption and pave the way for flexible, interoperable 5G deployments for network operators rather than reliance on radio network equipment from traditional vendors currently dominating the market, such as Ericsson, Huawei, and Nokia," Belkhit concludes.

These findings are from ABI Research’s 5G Massive MIMO Market Developments technology analysis report. This report is part of the company’s 5G, 6G, and Open RAN research service, which includes research, data, and ABI Insights. Based on extensive primary interviews, Technology Analysis reports present an in-depth analysis of key market trends and factors for a specific technology.